14 citations · 14 across the 2 of their papers we have counts for
3 papers
Weight Sparsity Complements Activity Sparsity in Neuromorphic Language Models
Rishav Mukherji, Mark Schöne, Khaleelulla Khan Nazeer +3
Activity and parameter sparsity are two standard methods of making neural networks computationally more efficient. Event-based architectures such as spiking neural networks (SNNs)…
Embodied Synaptic Plasticity with Online Reinforcement learning
Jacques Kaiser, Michael Hoff, Andreas Konle +8
The endeavor to understand the brain involves multiple collaborating research fields. Classically, synaptic plasticity rules derived by theoretical neuroscientists are evaluated in…
Long short-term memory and learning-to-learn in networks of spiking neurons
Guillaume Bellec, Darjan Salaj, Anand Subramoney +2
Recurrent networks of spiking neurons (RSNNs) underlie the astounding computing and learning capabilities of the brain. But computing and learning capabilities of RSNN models have…